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On the other hand, a problem is AI-Hard if and only if there is an AI-Complete problem that is polynomial time Turing-reducible to . This also gives as a consequence the existence of AI-Easy problems, that are solvable in polynomial time by a deterministic Turing machine with an oracle for some problem.
The problem for graphs is NP-complete if the edge lengths are assumed integers. The problem for points on the plane is NP-complete with the discretized Euclidean metric and rectilinear metric. The problem is known to be NP-hard with the (non-discretized) Euclidean metric. [3]: ND22, ND23
GraphQL is a data query and manipulation language that allows specifying what data is to be retrieved ("declarative data fetching") or modified. A GraphQL server can process a client query using data from separate sources and present the results in a unified graph. [2]
Selenium Grid is a server that allows tests to use web browser instances running on remote machines. With Selenium Grid, one server acts as the central hub. Tests contact the hub to obtain access to browser instances. The hub has a list of servers that provide access to browser instances (WebDriver nodes), and lets tests use these instances.
GSQL is a Turing-complete language that incorporates procedural flow control and iteration, and a facility for gathering and modifying computed values associated with a program execution for the whole graph or for elements of a graph called accumulators. These features are designed to enable iterative graph computations to be combined with data ...
Another related problem is the bottleneck travelling salesman problem: Find a Hamiltonian cycle in a weighted graph with the minimal weight of the weightiest edge. A real-world example is avoiding narrow streets with big buses. [15] The problem is of considerable practical importance, apart from evident transportation and logistics areas.
Toy problems were invented with the aim to program an AI which can solve it. The blocks world domain is an example for a toy problem. Its major advantage over more realistic AI applications is, that many algorithms and software programs are available which can handle the situation. [2] This allows to compare different theories against each other.
A special case of this problem is when G is a complete graph, each vertex v ∈ V corresponds to a point in a metric space, and the edge weights w(e) for each e ∈ E correspond to distances in the space. Put otherwise, the edge weights satisfy the triangle inequality. This variant is known as the metric Steiner tree problem. Given an instance ...